Data Analytics Strategy Kevin Tweddle Steven Simpson Large banks - PowerPoint PPT Presentation

Keys to a Successful Data Analytics Strategy Kevin Tweddle Steven Simpson

Large banks have built “Next Product to Buy” capabilities to predict customer need, pushing up to 60% of their sales of some products Most successful bank for each product is top 5 bank who has invested in analytics Instead of waiting for consumers to come to them, larger banks are aggressively predicting needs Helps larger banks capture a larger share of the 50% of consumers who added a financial product in 2015 SOURCE: US Banking Product Survey, 2014

DATA ANALYTICS – THE NEW COMPETITIVE ADVANTAGE TURN CHALLENGES INTO TRIUMPHS Increased Competition, Customer Churn Effective Marketing and Customer Satisfaction T H E B A N K I N G I N D U S T R Y Manage Regulatory Scrutiny Better Risk Management, Business Decisions; Strategic & Operational Transform Tight Margins & Low Loan Growth Enhance Revenue, Franchise Value & Culture

SEVEN-STEP PROCESS EXECUTIVE AND DEPARTMENTAL PARTNERSHIP IS KEY Executive Ownership Departmental Ownership Step Step Assess the “state of the union” Validate and corroborate the value #1 #2 Step Prio ioritize ze the busin iness ss opportuni nities s (sha hared d ownersh ship) p) #3 Revenue Growth Customer Insights and Acquisition Growth through market and customer analytics Strategic planning and organizational growth Bank Efficiencies Risk Mitigation Risk, fraud and compliance Branch transformation and information execution Step Step Align and engage the organization Create the execution plan #4 #5 Step Step Address and transform the culture Establish processes to monitor #6 #7 Become a Data Driven Organization, Fiserv, Inc. 2016

Step Prioritiz ioritize e the Bus usine iness ss Oppor ortunitie unities s #3 Grow Revenue Customer Insights and Acquisition Strategic Planning and Organizational Growth Growth Through Market and Customer Analytics Organica nicall lly Grow ow Wall llet et Share e Organiza nizatio iona nal l Growth owth New Market ket Asses essmen ment  Commercial Product and Pricing Review Strategic Research for New Markets  Campaign Management Planning   Deposit Product and Pricing Optimization Alternative Lending  Channel Adoption Analysis   Enterprise Execution Monitoring Prepaid Cards  Consumer Acquisition Strategies   Lending Growth/Cross-Sell Analysis Unbanked/Underserved Market  Customer Erosion & Attrition Analysis   Non-Interest Income Assessment  Customer Wallet Share Analysis Expan pand Market ket Share  Peer Performance and Benchmarking  Profitability Analysis  Marketing Strategy Review  Social Media Engagement Strategies  Mergers and Acquisition Opportunities  Small Business Growth Opportunity Small Business & Consumer Surveys   Top of Wallet Review Risk Mitigation  Wealth Management  Treasury Services Risk, Fraud and Compliance Bank Efficiencies Managing Risk, Fraud and Compliance Branch Transformation and Information Execution  ALLL Evaluation Efficie iciency ncy Opport ortunities unities Data-Driv iven en Execu ecution ion Initiativ iatives es  BSA Best Practices Review Back Office Operational Efficiency  Big Data Roadmap   Compliance Best Practices Review Branch Transformation  Business Intelligence Efficiencies   Credit Risk Assessment Branch Network Optimization  Governance and Trusted Data   Customer Delinquency Services Review Branch Process Efficiency Review  Data Warehousing Strategies   Fraud Rule Review Staff Optimization Review  Predictive Analytics   Risk Analysis and Scorecarding  Flexible Scheduling  Vendor Management Optimization Become a Data Driven Organization, Fiserv, Inc. 2016

SINGLE SOURCE OF TRUTH MAY BE THE GOAL – BUT FOCUS ON IMMEDIATE ROI Data Processors Service Corp. Transaction Data Mutual Funds Credit Cards Wealth ATM/EFT Travel Debit Card Insurance Checks & ACH Trust Digital: Internet & Mobile Integrated Stockholders Inter/Intra-net Data View Call Centers Raw Transaction Files Other Applications Outside Information Core: Loans & Deposits Lists Loan Origination Zillow/Realtor.com ALM System Loans Risk Management Demographics Commercial Geographic Profit SBA Social Media Custom Algorithms Mortgage Results of Regressions Consumer Credit Cards

THE 4 C’S Collect: A single source of the truth from multiple silos of data Cleanse: Resolve inconsistencies in data, relate data from multiple structures and systems Collec ect Compute: Profit, Primary Checking Algorithm, Retention Measure, LTV (from Zillow ZEstimate or Realtor.com), # of products per customer, algorithms for alerts (possible attrition in an important customer range, risk alerts). Identify data segments to assist lines of business achieve strategic Data ta Lak ake Consum ume Clea eanse goals: Mortgage no HELOC, CD but no credit products, Small Business & Commercial loans maturing in next 4-6 months (Above WAR, Below WAR (profitable vs. unprofitable), high number of checks – no positive pay. Income as a proxy, regression results back to segmentation, unique algorithms and unique by “market” Compute ute Consume: How the information is presented and used

TAKING ACTION Channel Message Time & Approach • Digital (e-mail, internet banking, Many opinions regarding When does specific channel and message mobile, etc.) what offer to make, how to combine to generate success? • In Branch deliver message, offer Through whom? • Traditional (print, stuff, mail) coupon or make special • Call Center offer, limited time only, etc. Time of year?... 2 days, 2 weeks, or 2 • In-Person / Officer Contact months into the customer’s relationship? Results Feedback Information from Digital Channels, CCM, CRM, Call Center, spreadsheets, etc. provide crucial information for assessment

ADVANCED ANALYTICS METHODOLOGY Building Recurring Best Practices Step p One Step p Two Step p Three ee Taking Action 4C Foundation Measure Action for each Opportunity via a specific Identify data segments of “untapped Define Success & Costs = ROI hurdle potential” or opportunity that help message, channel(s), and time Measure (Consider call center action vs. digital channel vs. achieve specific strategic goals (service, Track traditional marketing vs. control group) risk, growth, profit, retention) Adjust Build recurring best practices . . . right segment, right customer, right message at the right time

ADVANCED ANALYTICS METHODOLOGY Building Recurring Best Practices Feedback Loop 1: Adjust & Repeat Actions that perform over ROI hurdle while refining to “best” action: Feedback Loop 2: Human Element channel, message, and approach Identify best performers — use Learning Organization Theory to educate and lift performance of team Feedback Loop 3: Specific Algorithms Entrepreneurial Spirit? Profit, Household, Next Product Model, Loyalty Measure, Primary Checking, number of Products per Customer, etc. Feedback Loop 4: Regression New filters are applied and analyzed for further segmentation Via Random Forests or Binary Logistic Regression — identify Feedback Loop 5: Regression Results characteristics (products, services, trans, income, credit score, and other variables) — identify sub-segments with higher lead to Refinements probability of success and adjust Modify algorithms for unique characteristics of FI economy, products, market, customers Feedback Loop 6 Align incentives to best Actions

Keys to a Successful Data Analytics Strategy Kevin Tweddle Steven Simpson